A3: SPL Library Checkouts

Introduction

This data has been pulled from Seattle Open Data. I chose to observe the changes in checkout materials over the course of the last 5-6 years, the most popular publishers, the average checkouts each title has, and the publication year that has accumulated the most checkouts. For the checkout material trends, I was very curious to see how the numbers changed before, during, and after COVID. I was interested in learning which publishers are the most popular based on the checkouts because I realized I didn’t know many other publishers beside Penguin. The average checkouts and publication year with the most checkouts was something I didn’t have a hypothesis going into so I wanted to learn a bit more about this aspect. An introduction of the data and a description of the trends/books/items you are choosing to analyze (and why!) -Trends of physical and ebook checkouts over time -Average number of checkouts per item - -Publication year with the most checkouts. -Top 5 most popular subjects

Summary Information

Write a summary paragraph of findings that includes the 5 values calculated from your summary information R script

These will likely be calculated using your DPLYR skills, answering questions such as:

• What is the average number of checkouts for each item?
• What is the month or year with the most/least checkouts for a book that you’re interested in?
• What is the month or year with the most/least checkouts for ebooks?
• How has the number of print book checkouts changed over time?

Feel free to calculate and report values that you find relevant.

The Dataset

• Who collected/published the data?
  
• What are the parameters of the data (dates, number of checkouts, kinds of books, etc.)?
• How was the data collected or generated?
  
• Why was the data collected?
  
• What, if any, ethical questions do you need to consider when working with this data?
  
• What are possible limitations or problems with this data? (at least 200 words)

First Trends Over Time Chart

This chart illustrates the changes in physical book vs ebook checkouts from 2017-2023. We can see the very obvious change beginning in 2020 which coincides with the start of the COVID-19 pandemic. The sharp drop in physical book checkouts and the spike in ebook checkouts can be attributed to the need for social distancing and public spaces, like the library, not being open. Ebook checkouts can be made remotely, while physical book checkouts have to be done in person, which further explains the change that can be observed.

Second Trends Over Time Chart

Include a chart. Make sure to describe why you included the chart, and what patterns emerged

The second chart that you will create and include will show another trend over time of your variable/topic/interest. Think carefully about what you want to communicate to your user (you may have to find relevant trends in the dataset first!). Here are some requirements to help guide your design:

• Show more than one, but fewer than ~10 trends
  • For example, two books, or 5 different mediums
• You must have clear x and y axis labels
• The chart needs a clear title 
• You need a legend for your different line colors and a clear - legend title In your .Rmd file, make sure to describe why you included the chart, and what patterns emerged

When we say “clear” or “human readable” titles and labels, that means that you should not just display the variable name.

Here’s an example of how to run an R script inside an RMarkdown file:

Your Choice

The last chart is up to you. It could be a line plot, scatter plot, histogram, bar plot, stacked bar plot, and more. Here are some requirements to help guide your design:

• You must have clear x and y axis labels
• The chart needs a clear title 
• You need a legend for your different line colors and a clear legend title

Here’s an example of how to run an R script inside an RMarkdown file: